Jon Barron

I'm a principal research scientist at Google DeepMind in San Francisco, where I lead a small team that mostly works on NeRF. At Google I've worked on Glass, Lens Blur, HDR+, VR, Portrait Mode, Portrait Light, Maps, and Shopping. I did my PhD at UC Berkeley, where I was advised by Jitendra Malik. I've received the PAMI Young Researcher Award.

Email  /  ResearchGate

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Research

I'm interested in computer vision, deep learning, generative AI, and image processing. Most of my research is about inferring the physical world (shape, motion, color, light, etc) from images, usually with radiance fields. Some papers are highlighted.

[Paper/Project Title Here]
[Author 1], [Author 2], Hayley Coyle
[Venue], [Year]
project page / arXiv

One–two sentence abstract or description goes here. Keep it concise.

Miscellanea

Micropapers

Squareplus: A Softplus-Like Algebraic Rectifier
A Convenient Generalization of Schlick's Bias and Gain Functions
Continuously Differentiable Exponential Linear Units
Scholars & Big Models: How Can Academics Adapt?

Recorded Talks

Radiance Fields and the Future of Generative Media, 2025
View Dependent Podcast, 2024
Bay Area Robotics Symposium, 2023
EGSR Keynote, 2021
TUM AI Lecture Series, 2020
Vision & Graphics Seminar at MIT, 2020

Academic Service

Lead Area Chair, ICCV 2025
Lead Area Chair, CVPR 2025
Area Chair, CVPR 2024
Demo Chair, CVPR 2023
Area Chair, CVPR 2022
Area Chair & Award Committee Member, CVPR 2021
Area Chair, CVPR 2019
Area Chair, CVPR 2018

Teaching

Graduate Student Instructor, CS188 Spring 2011
Graduate Student Instructor, CS188 Fall 2010
Figures, "Artificial Intelligence: A Modern Approach", 3rd Edition

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